Google is building AI that can create its own art and music -- here's why that's important

Google introduced a new group dedicated to making artificial intelligence more creative at Moogfest, a four-day music and technology festival in Durham, North Carolina, Quartz first reported.

Called Magenta, the group will use its AI system TensorFlow to see if AI can be trained to create its own art, music, and video. The ultimate goal is to see if AI could give a listener “musical chills” by generating entirely new pieces of music, Quartz reported.

Google made TensorFlow open source in November so that any developer can use it. TensorFlow works by using deep learning, a process where machines learn to complete tasks all on their own, to recognise images. This is why Google Photos is so scary good at search — because it uses TensorFlow to recognise places based on popular landmarks or other characteristics.

The first project Magenta will launch is a program that allows researchers to import music data to allow the AI to get trained on musical knowledge.

So why is this important?

Google hasn’t expanded too much on the practical applications of training AI to be more creative. Douglas Eck, a Google researcher who introduced Magenta at Moogfest, said one use case of the program is to have AI that can create music to counteract stress, Quartz reported. So, if someone’s wearable detected their heart rate was elevated, the AI could play soothing music.

But from a bigger picture perspective, the ability to think creatively has long been understood as a specifically human skill. If AI were to truly crack creative thought, they would depart from being an extension of code written by a programmer to thinking on their own.

And that’s where we get into both the amazing and scary potential of AI. Right now, deep learning is still in its early phases. Machines can’t think entirely on their own, and probably won’t for some time.

But what Google’s AlphaGo taught us when it beat a world champion Lee Sedol at the game of Go, is that deep learning has vast potential to give machines the same thought capabilities of humans. One of the most fascinating takeaways from that Go tournament was when AlphaGo played a move that could only be described by AI experts as “creative.”

The move was so unexpected and brilliant that Sedol literally got up from his chair and left for a few minutes. Google’s AI was beginning to think so creatively, it was playing in a way human experts would never dream of.

If AI can master creative thinking, little by little, it inches closer to thinking like humans — or as we saw with AlphaGo, thinking in ways humans could potentially never dream of. Imagine the potential there beyond just creating artistic pieces — thinking like a human could have major applications in fields like driverless cars and robot assistants.